apex: A Go repository from mkapnick

Apex lets you build, deploy, and manage AWS Lambda functions with ease. With Apex you can use languages that are not natively supported by AWS Lambda, such as Golang, through the use of a Node.js shim injected into the build. A variety of workflow related tooling is provided for testing functions, rolling back deploys, viewing metrics, tailing logs, hooking into the build system and more.

Installation

On macOS, Linux, or OpenBSD run the following:

curl https://raw.githubusercontent.com/apex/apex/master/install.sh | sh

Note that you may need to run the sudo version below, or alternatively chown /usr/local:

curl https://raw.githubusercontent.com/apex/apex/master/install.sh | sudo sh

On Windows download binary.

If already installed, upgrade with:

apex upgrade

Runtimes

Currently supports:

Node.js
Golang
Python
Java
Rust
Clojure

Example projects for all supported runtimes can be found in _examples directory.

Features

Supports languages Lambda does not natively support via shim, such as Go
Binary install (install apex quickly for continuous deployment in CI etc)
Hook support for running commands (transpile code, lint, dependency management , etc)
Batteries included but optional (opt-in to higher level abstractions)
Environment variable population via command-line, file, or inline config
Idempotent deployments (checksums skip already-deployed code)
Multiple environments via project.ENV.json and function.ENV.json files
Configuration inheritance and overrides
Command-line function invocation with JSON streams
Command & function name autocompletion
Function name globbing (ex: apex deploy api_*)
Transparently generates a zip for your deploy
Project bootstrapping with optional Terraform support
Function metrics and cost analysis
Ignore deploying files with .apexignore
Function rollback support
Tail function logs
Concurrency for quick deploys
Dry-run to preview changes
VPC support

Backers

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Example

Apex projects are made up of a project.json configuration file, and zero or more Lambda functions defined in the "functions" directory. Here's an example file structure:

project.json
functions
├── bar
│   ├── function.json
│   └── index.js
└── foo
    ├── function.json
    └── index.js

The project.json file defines project level configuration that applies to all functions, and defines dependencies. For this simple example the following will do:

{
  "name": "example",
  "description": "Example project"
}

Each function uses a function.json configuration file to define function-specific properties such as the runtime, amount of memory allocated, and timeout. This file is completely optional, as you can specify defaults in your project.json file. For example:

{
  "name": "bar",
  "description": "Node.js example function",
  "runtime": "nodejs4.3",
  "memory": 128,
  "timeout": 5,
  "role": "arn:aws:iam::293503197324:role/lambda"
}

Now the directory structure for your project would be:

project.json
functions
├── bar
│   └── index.js
└── foo
    └── index.js

Finally the source for the functions themselves look like this in Node.js:

console.log('start bar')
exports.handle = function(e, ctx) {
  ctx.succeed({ hello: e.name })
}

Apex operates at the project level, but many commands allow you to specify specific functions. For example you may deploy the entire project with a single command:

$ apex deploy

Or whitelist functions to deploy:

$ apex deploy foo bar

Invoke it!

$ echo '{ "name": "Tobi" }' | apex invoke bar
{ "hello": "Tobi" }

See the Documentation for more information.

Notes

Apex collects usage metrics by default to help inform the team, allowing us to determine how commands and flags are used (if ever). No sensitive information is sent, no function names or alias names etc. To get a better idea of what is tracked run: